import cv2
import base64
import FacePlusPlusAPI

# Get a reference to webcam #0 (the default one)
video_capture = cv2.VideoCapture(0)

# Initialize some variables
face_locations = []
face_encodings = []
face_names = []
process_this_frame = True
facePP_API_Key = 'Dh_1F9Ax2b5feD7KkAc0nu46v3CVnRRX'
facePP_API_Secret = 'VYKh8ciikCPCrbg4Lm2iuJrcxouqDNXP'

def cv22base64(frame):
    # Convert captured image to JPG
    ret, buffer = cv2.imencode('.jpg', frame)

    # Convert to base64 encoding
    frame_as_text = base64.b64encode(buffer)

    return frame_as_text

while True:
    # Grab a single frame of video
    ret, frame = video_capture.read()

    # Resize frame of video to 1/4 size for faster face recognition processing
    small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)

    # Only process every other frame of video to save time
    if process_this_frame:
        # Find all the faces and face encodings in the current frame of video
        frame_as_text = cv22base64(small_frame)
        faces = FacePlusPlusAPI.faceppDetectAPI_base64(
            facePP_API_Key, facePP_API_Secret, frame_as_text
        )
        face_locations = [i["face_rectangle"] for i in faces]
        face_encodings = [i["face_token"] for i in faces]

        face_names = []
        '''
        for face_encoding in face_encodings:
            # See if the face is a match for the known face(s)
            matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
            name = "Unknown"

            # If a match was found in known_face_encodings, just use the first one.
            if True in matches:
                first_match_index = matches.index(True)
                name = known_face_names[first_match_index]

            face_names.append(name)
        '''

    process_this_frame = not process_this_frame


    # Display the results
    #for face_location, name in zip(face_locations, face_names):
    for face_location in face_locations:
        # Scale back up face locations since the frame we detected in was scaled to 1/4 size
        top = face_location["top"] * 4
        left = face_location["left"] * 4
        bottom = top + face_location["height"] * 4
        right = left + face_location["width"] * 4
        
        # Draw a box around the face
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

        # Draw a label with a name below the face
        #cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
        #font = cv2.FONT_HERSHEY_DUPLEX
        #cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

    # Display the resulting image
    cv2.imshow('Video', frame)

    # Hit 'q' on the keyboard to quit!
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release handle to the webcam
video_capture.release()
cv2.destroyAllWindows()